Stripe 数据揭示 AI 经济：增长、全球销售、定价与获客如何变化

简要描述Brief Description

人工智能经济内部：Stripe 的数据揭示了什么——Nilofer Rajpurkar，StripeInside the AI Economy: What Stripe's Data Reveals — Nilofer Rajpurkar， Stripe

目录Table of Contents

• 简介
  Intro
• 顶尖人工智能公司中的四种模式
  Four patterns among top AI companies
• AI 营收增长数据
  AI revenue growth data
• 通过 Link 推动消费者采用 AI
  Consumer AI adoption via Link
• 更快地构建
  Building faster
• 更快获得首位付费客户
  Faster time to first paid customer
• 演示：在 Claude 中添加 Stripe 支付功能
  Demo: adding Stripe payments in Claude
• 快速构建要点
  Takeaways for building fast
• 默认面向全球销售
  Selling globally by default
• Gamma的国际收入
  Gamma's international revenue
• AI 支出的来源
  Where AI spend is coming from
• 本地货币和支付方式
  Local currencies and payment methods
• AI经济的定价
  Pricing for the AI economy
• Replit 的混合定价模式
  Replit's hybrid pricing model
• 基于用量的定价原则
  Usage-based pricing principles
• 全新的市场推广策略
  New go-to-market motions
• 作为买家的渠道销售和代理商
  Channel sales and agents as buyers
• 代理访问 Stripe 文档的流量
  Agent traffic to Stripe docs
• 调整产品和收入基础设施
  Adapting product and revenue infrastructure
• 回顾
  Recap

简介Intro

大家早上好，感谢各位今天来到这里。我叫 Nil Farajj Par，是 Stripe 的产品负责人。我在我们的智能体与开发者体验团队工作，而这两者正日益融为一体。在 Stripe，我们与一些增长最快的 AI 公司合作，其中许多公司今天也在现场。我们得以近距离观察哪些做法奏效、哪些不奏效，以及这些公司如何实现规模化发展。所以今天，我很高兴向大家展示一些数据，分享我们观察到的情况……Good morning everyone and thank you for joining us here today. My name is Nil Farajj Par and I'm a product lead at Stripe. I work on our agent and developer experiences team and these are increasingly becoming one and the same. At Stripe, we work with some of the fastest growing AI companies, many of who are in this room today. And we get a front row seat into what's working, what's not, and how these companies scale. So today, I'm excited to show you some data from what we are seeing about

顶尖人工智能公司中的四种模式Four patterns among top AI companies

公司正在如何构建产品。我们看到顶尖 AI 公司普遍呈现出几种趋势。首先，它们的构建速度更快了。我想大家都能实时看到这一点。其次，它们从一开始就面向全球销售。第一天起，整个世界都是你的市场。第三，它们采用适应 AI 经济的定价方式。十年前，订阅制还是炙手可热的新模式，但如今已经行不通了。最后，它们能非常迅速地适应新的市场拓展方式。以上就是今天要讨论内容的大致概览。在我们开始之前，…how companies are building. So there's a few patterns that we're seeing across the top AI companies. First, they're building faster. I think we can all see this happening in real time. Next, they're selling globally by default. On day one, the entire world is your market. Third, they're pricing for the AI economy. 10 years ago, subscriptions was the hot new model on the block, but this just doesn't work anymore. And last, they're adapting to new go to market motions very quickly. So, this is a bit of a big picture of what we're going to talk about today. And before we jump in,

AI收入增长数据AI revenue growth data

我想先用一些数据让大家有个概念。2025年，我们看到 AI 营收增长了 120%。一年后，如今这个增幅达到了 175%，几乎是原来的三倍。所以，AI 营收增长并没有放缓。事实上，它正迅猛增长。今天我们要进一步聊聊这个话题。而那些 AI 公司领军人物的表现更是令人瞩目。以 Lovable 为例，他们报告称，八个月内营收达到 1 亿美元；又过了八个月，达到 4 亿美元。Cursor 两年内的年化营收达到 10 亿美元，仅仅三个月后就翻了一番，达到 20 亿美元。Anthropic 分享说，他们的营收从 2023 年 1 月的零起步，仅仅两年后就达到 10 亿美元，如今已达到 300 亿美元。这里的增长速度确实惊人。I want to ground us in a little bit of data. So in 2025, we saw AI revenue grow by 120%. A year later, we're seeing that now grow by 175%. Almost tripling. And so AI revenue growth isn't slowing down. In fact, it's on a tear. And uh this is uh what we're going to be uh talking a little bit more about today. And the folks who are at the top of those AI companies are even more remarkable. Take Lovable for example. They uh reported 100 million in eight months and then eight months later reported 400 million. Curser had a 1 billion run rate in two years and then just three months later doubled to 2 billion. Anthropic shared that they went from zero in January 2023 to a billion just two years later and now they're at 30 billion. So the growth rate here is really wild.

通过 Link 推动消费者采用 AIConsumer AI adoption via Link

但我们不仅在 B2B 数据中看到了这一趋势，在消费者数据中也看到了，消费者产品 Link 的数据同样如此。我们的 Link 数据显示，消费者对 AI 产品的采用率在短短一年内翻了一倍，从略低于 600 万增至超过 1,400 万。而且，这些客户的支出也在增加。我们的 Link 头部买家每月在 AI 工具和服务上的支出接近 360 美元，三个月前还只有 183 美元。这意味着在一个季度内几乎翻了一番。这笔支出超过了美国人用于手机、互联网和流媒体服务的平均总支出。但不同之处在于，用户并没有把 AI 当作一种可能明天就会取消订阅的流媒体服务。AI 工具正逐渐成为他们不可或缺的基础服务。所以，我们刚才谈了一些营收增长和采用率翻倍的情况，但……But we're not just seeing this in our B2B data. We're seeing this in our consumer data with our consumer product link as well. Our link data shows that consumer adoption of AI products doubled from just under 6 million to over 14 million in a span of a single year. And all of those customers are spending more as well. Our top link buyers are spending almost $360 a month on AI tools and services, up from $183 just three months ago. So that's almost doubling in the span of a quarter. This is more than the average American spends on phone, internet, and streaming services combined. But the difference is users aren't treating this like a streaming service they might drop tomorrow. AI tooling is becoming a critical utility for them. So, we talked a little bit about revenue growth and adoption doubling, but the

更快地构建Building faster

问题是，这一切增长背后的真正原因是什么？我想从之前提到的第一个趋势——更快地构建——说起，聊聊速度。就像如今你不再需要花几个月的工程时间才能接入支付一样，构建和发布软件也不再需要几个月的工程工作。到 2024 年末，iOS 应用的发布数量还在下降。随后，智能体编程工具开始崭露头角，增长率也大幅攀升至月环比 24%。特拉华州新企业的注册数量也呈现出非常相似的趋势。你可以看到，图表再次开始上扬，恰好与这些智能体编程工具的发布相吻合。大家都在谈论那些通过氛围编程打造新企业的非技术型创始人，而这确实是事实。question is what's really behind all of this growth? So, I'd love to jump in with our first pattern that I mentioned, which was building faster, and talk a little bit about speed. So just like you no longer need months of engineering to accept a payment, you no longer need months of engineering work to build and ship software. As of late 2024, iOS apps were releases were declining. And then you can see Agentic coding tools started to hit and that growth rate has grown quite uh substantially to 24% month- over-month. And we saw a very similar pattern with Delaware incorporations of new businesses as well. You can see where the graph starts to take off again aligning with the release of these agentic coding tools. So, everyone's talking about these non-technical founders who are vibe coding their way to new businesses and yeah, that's definitely true.

但我们觉得有意思的是，技术型创始人的占比也在增长，而且一年间增长了 7%。在座的很多人都是技术型创始人，你们现在一周内完成的事情，过去可能需要整个团队花上好几个月。这里真正值得注意的是，如今人人都能享受到这种速度。无论是借助开发者平台托管和构建产品的非技术型创始人，还是习惯在本地使用 Cursor 或 Claude 等工具的技术型创始人，构建并实现产品变现的速度从未如此之快。But what we found interesting is that the share of technical founders is actually growing as well and grew 7% in the span of a year. Many of you in this room are technical and you're probably doing in a week now what was taking teams entire months to do. And so what's really here uh salient here is that the speed is now available for everyone. For the nontechnical founders who are hosting and building using developer platforms or for the technical founders who are comfortable using things like cursor or claude locally. It's never been faster to build and monetize a product.

更快获得首位付费客户Faster time to first paid customer

我们实际上在一些与 Stripe 合作的开发者平台的数据中也看到了这一点。对于一些使用 Lovable、Forcell 或 Replit 构建产品的非技术用户，我们从数据中发现了一个有趣的现象：每一批新加入的月度用户，都能越来越快地获得付费客户。事实上，最新几批用户从推出产品到获得付费客户，所用时间不到六周。技术型创始人也能享受到这样的速度。随着我团队在 Stripe 推出 MCP 服务器、智能体技能和 Steering 等功能，这种体验应该会变得更好。所以……And we actually see this in some of the data of developer platforms who are partnering with Stripe. So for some of our nontechnical users who are building with lovable forcell or replet, we're seeing something interesting in the data. Each successive monthly cohort is getting to a paid customer faster and faster. In fact, our latest cohorts are getting from a product to a paid customer in less than six weeks. And that speed is available for a technical founder as well. So this should this experience gets better with some of the work my team is doing at Stripe releasing things like our MCP server and agent skills and steering. So

演示：在 Claude 中添加 Stripe 支付功能Demo: adding Stripe payments in Claude

我很乐意带你看一个例子。我有个新业务，想先做个快速评估，而且已经准备好添加支付功能了。所以我会打开 Claude，简单介绍一下我的业务模式，并告诉 Claude，我准备好添加订阅和开票支持了。Claude 正确地建议使用 Stripe 来构建支付功能；而当你加入我们的 MCP 技能、MCP 服务器和智能体技能后，它的能力会更强。这些信息能让 Claude 更好地建议如何构建 Stripe 集成。于是，它会使用我们的 Stripe 集成推荐器 MCP 工具，向我了解更多信息，以便为我构建合适的集成。它会询问我的客户所在的地区，从而判断是否应该推荐 Stripe Tax。它也知道应该推荐 Stripe Checkout，而不是 Card Element，因为 Checkout 的订阅集成效果更好。I'd love to take you through an example here. I've got a new business vibe check and I am ready to add payments. So I'm going to jump into Claude, describe a little bit about my business model and tell Claude I'm ready to add subscriptions and invoicing support. Claude correctly recommends building with Stripe and it gets p it gets more powerful when you add in our MCP skills and our MCP server and our agent skills. But that uh information makes Claude deliver a better recommendation of how it should build the Stripe integration. So it uses our Stripe integration recommener MCP tool to ask me a little bit of more information so that it can build the right integration for me. It's asking me where my customers are located so it can decide if it should recommend Stripe Tax or not. It knows to recommend Stripe Checkout over card elements because Checkout has a better subscriptions integration.

所以，我会直接告诉 Claude，我的客户分布在美国和欧盟。它告诉我，我可能应该使用 Stripe Tax——这是它从我们的智能体技能中学到的，因为在欧盟，我的数字订阅需要计算增值税，而我并非税务专家。所以，我会采用这个方案。你还可以看到，Claude 正在为我配置一个新的 Stripe 沙箱。这是通过一条新的 CLI 命令完成的，智能体无需我事先提供任何 Stripe 凭据，就能创建 Stripe 沙箱。它会自动获取沙箱的 API 密钥并安全地存储起来。这样一来，我就能直接获得一个可运行的端到端演示，无需退出 Claude，也能看到完整的结账流程。Claude 已经替我管理好了密钥，接下来正在查看我们其余的智能体技能，以确保给出正确的建议。So, I'll go ahead and tell Claude that my customers are located in both the US and the EU. And it tells me you probably want to go ahead and use Stripe Tax, which it learned from our agent skills, because in the EU, my digital subscriptions are subject to a VAT calculation and I am not a tax expert. So, I'll go ahead and take advantage of that. You can also see that Claude is provisioning a new Stripe sandbox for me. This is done via a new CLI command where an agent is able to create a Stripe sandbox without me needing to provide any Stripe credentials up front. It goes ahead and grabs API keys for the sandbox and stores them securely. And so now I'm able to get to a working endtoend demo without having to exit Claude and see that checkout working completely. So Claude's gone ahead and managed my keys for me and then it's taking a look through the rest of our agent skills to make sure it delivers the right recommendation.

现在它已经准备好询问我是否要使用 MCP 工具来创建产品目录。我会回答“是”。接下来我们直接跳到一个已完成的产品。现在我的网站上有了一个订阅按钮。我点击“订阅”，就能看到一个已完全可用的结账表单，可以用来测试。我输入一些测试银行卡信息，然后点击“订阅”。我可以看到测试支付流程正在进行。好了，现在我可以看到客户尝试订阅我的网站时会经历的完整端到端流程，而且完全不必离开 Claude。It's now ready to ask me if I want to use the MCP tools to go ahead and build out my product catalog. And I'll say yes. And we'll skip a little forward to a completed product here. So now I have a subscription button on my website. I'll go ahead and click subscribe. And I can see a fully working checkout form ready to go for me to test this out. I'll provide some test card details. Go ahead and click subscribe. And I can see that test payment process. And there you go. Now I can see a full endto-end flow of what my customers will see when trying to subscribe to my website without ever having to have left claude.

快速构建的要点Takeaways for building fast

那么，这在实践中对你意味着什么？首先，你需要把开发者效率放在首位。那些做得最好的团队都将此视为优先事项，而不是事后才考虑的事情，因为构建周期正变得越来越短。我们正在打造的工具，比如 MCP 服务器、智能体技能与引导机制，以及针对资金转移等敏感操作的智能体护栏，都应该能在整个过程中为你提供帮助。 接下来，你需要同时进行构建、销售和迭代。先构建产品、过一段时间才接触首位客户的老套路，对于我们如今所处的现实来说太慢了。最优秀的团队会并行推进这些工作。 最后，面对自建还是采购的抉择时，顶尖的 AI 公司两者兼顾：自行构建那些他们认为能形成差异化优势的东西，同时采购所需的基础组件来实现这些优势。So what does this mean for you in practice? First, you need to obsess over developer productivity. The best teams who are doing this are treating this like a priority and not as an afterthought because build times are compressing to be smaller and smaller. Our tools that we're building like our MCP server, our agent skills and steering as well as agent guard rails for sensitive uh actions like money movement should help you throughout this process. Next, you need to build, sell, and iterate all at the same time. The old playbook of building and taking a while before you get to your first customer just is too slow for the reality that we're living in. The best teams are doing this in parallel. And lastly, when confronted with build versus buy decisions, top AI companies are doing both. They're building the things that they've identified are uh differentiators for them and buying the building blocks that they need to enable that.

默认面向全球销售Selling globally by default

好，快速构建是一回事，但在哪里销售同样重要。我们来聊聊默认面向全球销售意味着什么。过去的做法是，作为一家 SaaS 公司，我会专注于本土市场，等觉得时机成熟了，再开始拓展其他市场。我可能会去伦敦招一位总经理，开设一间新办公室，转眼间就成了一家国际公司。但这种做法已经行不通了，对于我们看到的顶尖 AI 公司来说，这样做也太慢了。按照传统的 SaaS 模式，你可能第一年进入 25 个国家，到第三年进入 50 个国家。但顶尖 AI 公司远远超越了这个水平。第一年，它们就在 48 个国家销售；到第三年，业务已经遍及 120 个不同的国家。而这并不是说它们在这些国家设有实体据点。Okay, so building fast is one thing, but where you sell is just as important. So let's talk about what it means to sell globally by default. The old pattern here was that as a SAS company, I would focus on my home market and then once I feel good, start to expand into some other markets. A I might go hire a GM in London, build a new office and boom, now I'm an international company. But that just doesn't work anymore and is far too slow for what we're seeing with the top AI companies. The old SAS model would have had you in 25 countries in year one and then 50 countries by year three. But our top AI companies are blowing that out of the water. In year one, they're selling in 48 countries and by year three, they're in 120 different countries. And this isn't about having a presence in those countries.

这关系到那些地方真正付费的客户。It's about real paying customers in those places.

Gamma 的国际收入Gamma's international revenue

Gamma 就是一个很好的例子。也许他们确实如此。让我来介绍一下他们。他们是一家由 AI 驱动的幻灯片和网站构建工具公司，据报告，他们在第一年就实现了超过 1 亿的收入。虽然他们总部设在旧金山，但他们的大部分收入实际上来自美国以外的地区。所以我们看到，他们不再是个例，而是顶尖 AI 公司构建业务的常态。可能会有一些幻灯片传回来。不管怎样，我会继续讲。我们实际上看到，在这些顶尖 AI 公司中，48% 的收入来自其本土市场以外的地区。这意味着，顶尖 AI 公司赚取的每一美元中，近一半都来自海外。我们真正注意到的是，这一比例从三年前的 33% 上升至如今的水平，说明全球收入不再只是商业模式的额外加分项。Gamma is a great example of this. Perhaps they are. Let me tell you about them. So they uh are an AI powered slide and website builder and they've reported over a 100 million in revenue in their first year. Although they're based in SF, they're the majority of their revenue is actually coming from outside of the United States. And so what we're seeing is that they're not the exception anymore. They're actually the rule of how these top AI companies are building. Might get some slides back. I'll keep talking anyway. And what we're seeing is actually across those top AI companies, 48% of that revenue is coming from outside of their home markets. So that's nearly half of every dollar that top AI companies are making. And so what we're really noticing here with this being up from 33% 3 years ago is that global revenue is no longer a bonus for your business model.

这实际上正变得对你的业务如何赚钱至关重要。也许我们可以在幻灯片上展示一下怎么做。好吧。好的。那么，我继续带大家过一遍这里的内容。嗯，我们来谈谈……It's actually becoming critical for how your business makes money. How we do it on slides. maybe. All right. Okay. So, I'll keep I'll keep walking us through here. Um, let's talk

AI 支出来源在哪里Where AI spend is coming from

简单谈谈我们在 Stripe 上看到的一些数据，看看人们在哪些地方的 AI 消费最高。我本来想给你们展示一张炫酷的地图，就当看过了吧。我们发现，消费最高的国家中，有些也是 GDP 最高的国家。这不意外吧？比如美国、日本和德国。不过，更有意思的是一些新兴的消费热点，也就是人们花费最多的地方，比如巴西、印度和韩国。由此可见，这些国家对 AI 服务和工具有需求。a little bit about some data that we're seeing uh of where people are spending the most on AI on Stripe. I'd show you a fancy map, so just pretend. Um, what we're seeing is that some of the highest spend is coming from countries with the highest GDP. Unsurprising, right? So, countries like the United States, Japan, Germany. But what's more interesting is some of the hot spots that are emerging uh of where people are spending the most. This is in countries like Brazil and India and South Korea. And so it's clear that there's demand for AI services and tooling in those countries.

本地货币和支付方式Local currencies and payment methods

但如何确保你真正做到这一点？一种确保做到这一点的方法，就是满足客户的预期：用他们熟悉的货币定价，并支持他们希望使用的本地支付方式。事实上，我们发现，以当地货币显示价格的公司，其跨境收入几乎高出 18%；而至少支持一种本地支付方式的公司，转化率则提升了 7% 以上。借助我们的 Stripe 技能，智能体也越来越懂得如何做到这一点。正如我们演示过程中所看到的，Stripe 智能体建议我使用 Stripe Tax，但这还不止于此。通过这些技能，智能体知道应该支持以当地货币显示价格和本地支付方式，从而帮助你优化在这些本地市场的销售表现。But how do you make sure that you are capturing it? One way that we make that you can make sure you do this is by meeting your customers expectations and selling in currency that matches what they're used to and local payment methods that they know you want. they want you to support. In fact, we saw that companies who present prices in local currency saw almost 18% higher crossber revenue and that companies who present and support at least one local payment method saw a greater than 7% conversion uplift and agents are increasingly knowing how to do this with our Stripe skills. You saw as we walked through the demo, Stripe uh the agent recommended that I use Stripe Tax, but it's more than just that. Through our skills, an agent knows that they should support local currency presentation and local payment methods so that you can help so they can help you optimize for selling in those local markets.

你不再需要成为你所销售市场的专家，因为 Stripe 已经是这方面的专家，也能为你提供帮助。因此，以下几点可以帮助你检验业务是否已做好全球化准备。首先，针对你计划开展销售的市场，调整价格和支付方式。其次，自动收取税款，因为没人想因为不了解税务规则而惹上麻烦。最后，按国家/地区跟踪收入和转化表现，并毫不留情地持续优化。You no longer need to be an expert in the markets that you are selling in because Stripe already is and can help you with that. So, here's a few things to think about to pressure test your global readiness. First, localize your prices and payment methods in the markets that you're going to be go going to be selling in. Next, automate tax collection because nobody wants to get in trouble because they didn't know the tax rules. And last, track your revenue and conversion performance by countries and optimize ruthlessly.

AI经济的定价Pricing for the AI economy

好，我们来聊聊 AI 经济下定价方式正在发生怎样的变化，因为我们过去习惯的模式已经不太适用了。我们过去会把软件的价值看作一种工具。你可能会花 1 万美元购买 Zendesk，然后再去雇一些客服代表，实际处理涌入的客户支持工单。但 AI 从根本上改变了我们看待这种价值的方式。随着产品具备代理式能力，我们开始能够看到它们带来的实际价值，并可以把它们的价值视为成果的产出。比如，Intercom 的 Finn 会为你管理并解决客户支持请求。因此，当我们开始思考这种新模式时，这种价值就开始变得可衡量，可以用解决的问题数量、提交次数、完成的工作流等指标来统计；而我们也因此不得不开始思考如何为产品定价，才能真正体现这种价值。Okay, so let's talk a little bit about how pricing is changing for the AI economy because the models we're used to aren't quite working anymore. We're used to thinking about the value of software as a tool. You might spend 10k on Zenesk and then go buy go hire some customer support representatives to actually handle the customer support tickets that are coming into you. But AI is fundamentally shifting how we think about that value. As products gain agentic uh capabilities, we're actually able to see them deliver on value and we can think about their value as a as an output of that result. For example, Intercom's Finn actually goes and manages and resolves customer support requests for you. So, as we start thinking about this new model, that value actually starts to become measurable, counted in things like resolutions, commits, workflows completed, and then we're forced and incentivized to start thinking about how we price our products to actually communicate that value.

而且，重新定价这件事并不新鲜。每次出现重大技术变革时，我们都经历过这样的过程。最初是本地部署软件，安装后基本保持稳定，因此一次性许可证很合理。但后来我们转向云端，软件持续更新，订阅模式也就开始变得合适。现在你大概正等着我告诉你，AI 适合采用什么模式。那么，我有一个好消息和一个坏消息。坏消息是，我们还处于早期阶段，仍在摸索。好消息是，我们从 Stripe 的数据中看到了一些逐渐显现的规律。以 Replit 为例……And thinking about this repricing isn't new. We've done this every time we've had a major technology shift. We started with the on-prem software where things were pretty stable after an install and so a one-time license made sense. But then we moved to cloud and your software was getting updated continuously and so a subscription model started to fit the bill. And about now is where you expect for me to tell you what the right model for AI is. So I've got some good news and some bad news. The bad news is we're in the early innings. We're still figuring this out. But the good news is we are seeing some patterns emerge amongst our stripe data. Take replet for

Replit 的混合定价模式Replit's hybrid pricing model

例如，Replet 是一个已发展近十年的开发者平台。随着智能代理编程真正兴起，他们重新调整了产品方向，重新思考定价策略，此后实现了火箭式增长。他们最初采用统一订阅模式，后来随着 AI 成为产品的核心，又加入了额度。订阅为用户提供可预测性，用量计费则帮助他们按价值收费。因此，Replet 的目标是今年实现 10 亿美元的年度经常性收入（ARR）。而以这种方式思考定价的并非他们一家。按用量计费正成为所有销售 AI 服务的企业的关键。事实上，《福布斯》AI 50 榜单中三分之二的公司都采用了某种形式的按用量定价，许多公司也提供了类似 Replet 的混合模式。订阅部分有助于巩固你与客户的关系，并为他们提供可预测性。example, a developer platform that has been around for almost a decade. When agentic coding really started to take off, they re pivoted their product and rethought their pricing and have since seen hockey stick growth. They started with a flat subscriptions model and then added on credits as AI became core to their product. subscriptions for predictability for their users and then usage for value capture. And so the result is that Replet is aiming for a 1 billion ARR this year. And they're not alone in thinking about their pricing in this way. Usagebased billing is becoming critical for anybody selling AI services. In fact, two and three of the Forbes AI50 companies have some form of usagebased pricing and many are delivering that sort of hybrid model that Replet is. The subscription piece helps you anchor in your relationship with your customer and provide them that predictability.

而基于用量计费的部分，则有助于随着客户不断成长、使用量不断增加而扩展。And the usage based pill uh billing piece helps scale with the usage uh that your customer experiences as they grow.

基于用量的定价原则Usage-based pricing principles

因此，知道需要采用基于使用量的模式是一回事，但实际操作中这意味着什么？这里有几个值得考虑的原则。首先，用客户熟悉的语言来定价。开发者思考的是 token，企业思考的是席位。但越来越多的人开始接触并习惯按使用量计费。因此，想想如何用定价的方式，传达用户所获得的价值。接下来，要让客户在账单寄到之前就能实时了解支出。没人打开电费账单时会想：“咦，居然比我预想的便宜。”你也不希望你的产品用户遇到同样的情况。因此，务必实时向他们展示使用情况，让他们清楚最终要花多少钱。So knowing you need to be usage based is one thing, but what does that mean in practice? Here's a few principles to think about. First, price in your customers language. Developers think in tokens. Enterprises think in seats. But more and more everyone is being uh exposed to and becoming comfortable with consumption. And so think about how you can communicate the value that your uh users are receiving in the way that you communicate the price. Next, you want to give your customers real time spend visibility before they get their bill. No one has opened up their electric bill and thought, "Huh, that's cheaper than I expected." And you don't want the same to be true with users of your products. So, make sure that you're communicating their real-time usage so that they understand what the the cost is going to be at the end of the day.

这不只是锦上添花，而是防止用户流失的关键。最后，考虑出售积分，而不是按成本收费。让用户预先一次性付费，将钱兑换成你产品中的积分。这样，他们使用产品时，关注的就是自己获得的价值，而不是每次操作花了多少钱。This is not just a nice to have. It's critical to prevent user churn. Lastly, think about selling credits, not costs. Have your users exchange money for credits on your product upfront and one time so that when they're using your product, they're thinking about the value that they're they're experiencing and not the dollars and cents for every action that they're taking.

新的市场进入策略New go-to-market motions

好，我们再来看一个趋势：公司，尤其是顶尖 AI 公司，如何适应新的市场推广方式。过去的模式是，先打造一款产品，再建立一套产品驱动的增长体系，期待公司和初创企业自然而然地发现并使用你的产品。几年后，等你找到产品市场契合度，就会转向销售驱动的模式。我们看到，这个过程对于如今新公司的发展来说实在太慢了。事实上，许多公司在创立的第一年就开始推动企业销售。例如，Cursor 在 2023 年起步时采用的是面向开发者的自助服务模式，但他们很快意识到，需要建立销售驱动的业务模式，才能拿下企业合同。Okay, one more trend for us to walk through here and this is how companies or top AI companies are adapting to new gotom market motions. So the old pattern here was you'd build a product, you'd have a productled uh growth uh system here and you would expect companies and startups to find your product organically. Then at some point in a few years you'd transition to salesled as you found product market fit. And what we're seeing is that process is just entirely too slow in the way that new companies are building. And many companies are actually starting an enterprise sales motion early in year one of their uh build. Cursor, for example, started out in 2023 as a self-s serve model for developers, and they quickly realized they needed to build a salesled motion so that they could go land enterprise contracts.

如今，Cursor 已经建立起一套令人印象深刻的销售驱动型增长模式，而其他公司过去要花数月甚至数年才能建立起这样的模式。Now, Cursor has built a really impressive salesled motion that would have taken companies before months, if not years, to build.

渠道销售和作为买家的代理商Channel sales and agents as buyers

而这并不是我们看到的唯一变化。没错，销售主导型流程的启动时间越来越早，但我们也看到新的销售模式不断涌现。例如，渠道销售在整个业务中的占比正在大幅提升。用户正通过云服务提供商直接购买 Anthropic 和 OpenAI 的服务。许多这类 AI 产品实际上也开始推出市场，让其他人也能通过这些市场销售产品。接下来就是那个价值十亿美元、甚至可能高达一万亿美元的问题：我们该如何适应新的买家——智能体？几十年来，我们在为产品定价时一直在琢磨人类心理，比如定价 9.99 美元而不是 10 美元，或采用“好、更好、最好”的定价体系。但问题是，智能体根本不在乎这些花招。And that's not the only shift we're seeing. Yes, you're starting salesled emotions a lot earlier, but we're also seeing new motions emerge. For example, channel sales are becoming a much larger piece of the equation. Users are buying anthropic and open AI services directly through their cloud providers. And many of these AI uh uh products are actually introducing marketplaces so that others can do the same and sell through them as well. And then there's the billion or perhaps trillion dollar question. How do we adapt for our new buyers, agents? We've spent decades thinking about human psychology when pricing products, things like $9.99 instead of $10, good, better, best systems. But the thing is, agents don't care about any of these tricks.

访问 Stripe 文档的智能体流量Agent traffic to Stripe docs

这张图可能最能说明这一点。2025 年，我们看到访问 Stripe 文档的智能体流量在一年内增长了 10 倍。这张图展示了人类和智能体访问文档的流量。正如你所看到的，这两条线正在逐渐靠拢。到 2026 年底，我们预计智能体阅读的文档将远多于人类，而……This chart might be the most illustrative of this. So in 2025, we saw agent traffic to Stripe docs 10x in a single year. This chart is showing human traffic to docs and agent traffic to docs. And you, as you can see, those lines are converging. And by the end of 2026, we expect that agents are going to be reading far more docs than humans and

调整产品与收入基础设施Adapting product and revenue infrastructure

把它用作我们产品的发现机制。下面这点大多数人都低估了。当你开始采用新的市场进入策略时，这只是冰山一角。还有很大一部分工作需要在底层同步推进。每次采用新的市场进入策略，你都必须调整产品。你需要考虑，针对这些新渠道，入门引导要如何改变。定价模式也需要调整，而且组织必须做好支持准备。服务企业客户，与服务大量长尾自助服务客户有很大不同。因此，新的市场进入策略实际上意味着公司底层商业模式的转变。另一个不同之处在于，公司实际构建收入基础设施的方式。过去，公司会把各种东西逐步拼接起来；当业务发展缓慢时，这样做还行得通。using that as discovery mechanisms for our products. So here's the part that most people underestimate. When you go to adopt new go-to market motions monitor, that's just the tip of the iceberg. There's a whole section that needs to move underneath. Every time you adopt a new motion, you have to adapt your product. You need to think about how onboarding is now going to change for those new channels. Your pricing model needs to adjust and your organization needs to be ready to support this. Supporting an enterprise customer is much different than supporting the long tale of self-s serve. So a new GTM motion really means a shift in the underlying business model of your company. Another place that's different is how uh companies actually build revenue infrastructure. Previously they would bolt things on and when you were going slowly this was okay.

当你试图在短短几个月内压缩完成原本需要 10 年才能搭建的市场拓展基础设施时，这些工具之间的衔接问题就会变得非常明显，并成为一种负担。思考客户如何在这些渠道之间流动时，以下是市场拓展策略中需要考虑的几点。你需要清楚说明用户如何从自助服务转向企业级服务，以及在这一过程中定价模式会如何变化。你应该构建统一的业务系统，也就是说，用一种方式呈现客户，建立一个产品目录，并在这些服务之间采用统一的数据模型。最后，你还需要考虑如何为作为买家的智能体进行设计。智能体应该能够在没有人工参与的情况下发现、评估并启用你的产品。When you start to compress 10 years of go to market infrastructure into the matter of months the seams between each of these tools starts to become really really apparent and becomes a liability. As you're thinking about your customers as channel uh moving across any of these channels, here are some things to think about in your go to market motions. You need to have a clear articulation of how people move from self-s serve to an enterprise and how the pricing model changes when they do. You should build unified business systems. This means one representation of your customer, one product catalog, and unified data models across each of these services. And lastly, you need to think about how you're designing for agents as buyers. An agent needs to be able to discover, evaluate, and activate your product without a human in the loop.

回顾Recap

好了，我们聊了顶尖 AI 公司如今如何以不同方式构建产品、销售、定价，并调整市场进入策略：以小时和天为单位更快地构建产品，在第一天就面向 42 个国家销售，按价值定价，并且在完成 A 轮融资之前就启动企业销售。对于产品构建者来说，现在从未有过如此令人兴奋、如此有趣的时刻。我在 Stripe 的团队致力于确保我们打造出合适的产品，助力你实现变现并更快地构建产品。如果你对我们如何在这个过程中为你提供更好的支持有任何反馈或疑问，我很乐意与你交流。非常感谢。Okay, so we've talked about how the top AI companies are building, selling, pricing, and adapting to go to market motions differently now. building faster in the matter of hours and days, selling in 42 countries on day one, pricing for value, and starting an enterprise sales motion before they've raised their series A. It's never been a more exciting or fun time to be a builder. My team at Stripe is focused on how we make sure that we're building the right things to empower you to monetize and build faster. So, if you've got any feedback or questions on how we can better support you in that journey, love to chat. Thank you so much.